code: def repulsion_tensor(basis_functions):
      r"""Return a function that computes the electron repulsion tensor for a given set of basis
      functions.
  
      Args:
          basis_functions (list[~qchem.basis_set.BasisFunction]): basis functions
  
      Returns:
          function: function that computes the electron repulsion tensor
  
      **Example**
  
      >>> symbols  = ['H', 'H']
      >>> geometry = np.array([[0.0, 0.0, 0.0], [0.0, 0.0, 1.0]], requires_grad = False)
      >>> alpha = np.array([[3.42525091, 0.62391373, 0.1688554],
      >>>                   [3.42525091, 0.62391373, 0.1688554]], requires_grad=True)
      >>> mol = qml.qchem.Molecule(symbols, geometry, alpha=alpha)
      >>> args = [alpha]
      >>> repulsion_tensor(mol.basis_set)(*args)
      array([[[[0.77460595, 0.56886144], [0.56886144, 0.65017747]],
              [[0.56886144, 0.45590152], [0.45590152, 0.56886144]]],
             [[[0.56886144, 0.45590152], [0.45590152, 0.56886144]],
              [[0.65017747, 0.56886144],[0.56886144, 0.77460595]]]])
      """
  
      def repulsion(*args):
          r"""Construct the electron repulsion tensor for a given set of basis functions.
  
          Permutational symmetries are taken from [D.F. Brailsford and G.G. Hall, International
          Journal of Quantum Chemistry, 1971, 5, 657-668].
  
          Args:
              *args (array[array[float]]): initial values of the differentiable parameters
  
          Returns:
              array[array[float]]: the electron repulsion tensor
          """
          n = len(basis_functions)
          tensor = qml.math.zeros((n, n, n, n))
          e_calc = qml.math.full((n, n, n, n), np.nan)
  
          for (i, a), (j, b), (k, c), (l, d) in it.product(
              enumerate(basis_functions), repeat=4
          ):
              if qml.math.isnan(e_calc[(i, j, k, l)]):
                  args_abcd = []
                  if args:
                      args_abcd.extend(
                          [arg[i], arg[j], arg[k], arg[l]]
                          for arg in args
                      )
                  integral = repulsion_integral(
                      a, b, c, d, normalize=False
                  )(*args_abcd)
  
                  permutations = [
                      (i, j, k, l),
                      (k, l, i, j),
                      (j, i, l, k),
                      (l, k, j, i),
                      (j, i, k, l),
                      (l, k, i, j),
                      (i, j, l, k),
                      (k, l, j, i),
                  ]
  
                  o = qml.math.zeros((n, n, n, n))
                  for perm in permutations:
                      o[perm] = 1.0
                      e_calc[perm] = 1.0
                  tensor = tensor + integral * o
          return tensor
  
      return repulsion
  
file_path: pennylane/pennylane/qchem/matrices.py
imports: import itertools
  import numpy
  import pennylane
  from .integrals import attraction_integral, kinetic_integral, moment_integral, overlap_integral, repulsion_integral
label_desc: Use image node_id 6 for calling a global function with example usage: repulsion_tensor(basis_functions) and returns: repulsion, tensor